Intelligence Science: Leading the Age of Intelligence covers the emerging scientific research on the theory and technology of intelligence, bringing together disciplines such as neuroscience, cognitive science, and artificial intelligence to study the nature of intelligence, the functional simulation of intelligent behavior, and the development of new intelligent technologies. The book presents this complex, interdisciplinary area of study in an accessible volume, introducing foundational concepts and methods, and presenting the latest trends and developments. Chapters cover the Foundations of neurophysiology, Neural computing, Mind models, Perceptual intelligence, Language cognition, Learning, Memory, Thought, Intellectual development and cognitive structure, Emotion and affect, and more. This volume synthesizes a very rich and complex area of research, with an aim of stimulating new lines of enquiry.

The technology of Artificial Intelligence is here, and moving fast, without ethical standards in place. A Blueprint for the Regulation of Artificial Intelligence Technologies leans on classical western philosophy for its ethical grounding. Values such as conscience, rights, equity, and discrimination, establish a basis for regulatory standards. Multiple international agencies with governing interests are compared. The development of ethical standards is suggested through two new non-governmental organizations (NGOs). The first is to develop standards that evolve from practice, while the second acts as an ombudsman to settle abuse. Both NGOs are envisioned to cooperate with regulators. More than seeking a perfect solution, the book aims to balance the tension between conflicting interests, with the goal to keep this dangerously wonderful technology under global human control. For that to materialize, the technology needs to have a seat on the table of global ethics. The final chapter lists fourteen thinking points to achieve an ethics balance for new technologies.

For computer-security courses that are taught at the undergraduate level and that have as their sole prerequisites an introductory computer science sequence (e.g., CS 1/CS 2). A new Computer Security textbook for a new generation of IT professionals. Unlike most other computer security textbooks available today, Introduction to Computer Security, 1e does NOT focus on the mathematical and computational foundations of security, and it does not assume an extensive background in computer science. Instead it looks at the systems, technology, management, and policy side of security, and offers students fundamental security concepts and a working knowledge of threats and countermeasures with "just-enough" background in computer science. The result is a presentation of the material that is accessible to students of all levels.

Today, network technology is ubiquitous. Whether at home or on the move, at work or at play, the modern data network is a part of our daily lives. Streaming video, social media and web browsing are just a few of the popular applications that rely on the network, and this list will continue to grow with autonomous vehicles, virtual reality and others, each with their own unique needs. To address the challenges of the demand for these services, the network must continually evolve with new technologies. However, determining which technologies are worth focusing on today is difficult, and the issues which they represent, and address are often complex. In Network Horizons Emerging Technologies and Applications 2018 - 2019 Edition, the author highlights key areas of interest for network technology, helping the reader to identify those of the highest importance by explaining the what, why and when of each of these important areas of development to make sure they and their business are prepared for the future.

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more.

Quantitative Atomic-Resolution Electron Microscopy, Volume 217, the latest release in the Advances in Imaging and Electron Physics series merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods. Chapters in this release include Statistical parameter estimation theory, Efficient fitting algorithm, Statistics-based atom counting , Atom column detection, Optimal experiment design for nanoparticle atom-counting from ADF STEM images, and more.

Introduction to Information Systems, 9th Edition delivers an essential resource for undergraduate business majors seeking ways to harness information technology systems to succeed in their current or future jobs. The book assists readers in developing a foundational understanding of information systems and technology and apply it to common business problems. This International Adaptation covers applications of the latest technologies with the addition of new cases from Europe, Middle East, Africa, Australia, and Asia-Pacific countries. It focuses on global business environment for students to understand the norms of using technology while operating on online platforms for exploring new avenues in different geographical locations. The book includes real business scenarios of how latest technologies such as Big Data, Cloud Computing, Blockchain, and IoT are perceived and adopted across countries. New cases highlight key technology issues faced by organizations such as designing and implementing IT security policies, dealing with ethical dilemma of securing customer data, moving IT infrastructure to cloud, and identifying how AI can be used to improve the efficiency of business operations.

Businesses have had to face many challenges due to the COVID-19 pandemic; to survive in the changing landscape, they had to adapt quickly and implement new tactics and best practices to stay competitive. Networking is one of the many areas that looks vastly different in a post-pandemic world and companies must understand this change or risk falling behind. Further study is required to uncover the various difficulties and potential future directions of networking and innovation within the business landscape. The Handbook of Research on Digital Innovation and Networking in Post-COVID-19 Organizations provides a thorough overview of the ways in which organizations have had to change and adapt to the new business environments and considers how networking looks different in a post-COVID-19 world. Covering key topics such as organizational structures, consumer behavior, teleworking, and collaborations, this major reference work is ideal for managers, business owners, industry professionals, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.

Instruction on operating system functionality with examples incorporated for improved learning With the updating of Silberschatz's Operating System Concepts, 10th Edition, students have access to a text that presents both important concepts and real-world applications. Key concepts are reinforced in this global edition through instruction, chapter practice exercises, homework exercises, and suggested readings. Students also receive an understanding how to apply the content. The book provides example programs written in C and Java for use in programming environments.

This book examines the tangled responsibilities of states, companies, and individuals surrounding human rights in the digital age. Digital technologies have a huge impact – for better and worse – on human lives; while they can clearly enhance some human rights, they also facilitate a wide range of violations. States are expected to implement efficient measures against powerful private companies, but, at the same time, they are drawn to technologies that extend their own control over citizens. Tech companies are increasingly asked to prevent violations committed online by their users, yet many of their business models depend on the accumulation and exploitation of users’ personal data. While civil society has a crucial part to play in upholding human rights, it is also the case that individuals harm other individuals online. All three stakeholders need to ensure that technology does not provoke the disintegration of human rights. Bringing together experts from a range of disciplines, including law, international relations, and journalism, this book provides a detailed analysis of the impact of digital technologies on human rights, which will be of interest to academics, research students and professionals concerned by this issue.

For undergraduate-level courses in Signals and Systems. This comprehensive exploration of signals and systems develops continuous-time and discrete-time concepts/methods in parallel -- highlighting the similarities and differences -- and features introductory treatments of the applications of these basic methods in such areas as filtering, communication, sampling, discrete-time processing of continuous-time signals, and feedback. Relatively self-contained, the text assumes no prior experience with system analysis, convolution, Fourier analysis, or Laplace and z-transforms.

Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing.

The advent of connected, smart technologies for the built environment may promise a significant value that has to be reached to develop digital city models. At the international level, the role of digital twin is strictly related to massive amounts of data that need to be processed, which proposes several challenges in terms of digital technologies capability, computing, interoperability, simulation, calibration, and representation. In these terms, the development of 3D parametric models as digital twins to evaluate energy assessment of private and public buildings is considered one of the main challenges of the last years. The ability to gather, manage, and communicate contents related to energy saving in buildings for the development of smart cities must be considered a specificity in the age of connection to increase citizen awareness of these fields. The Handbook of Research on Developing Smart Cities Based on Digital Twins contains in-depth research focused on the description of methods, processes, and tools that can be adopted to achieve smart city goals. The book presents a valid medium for disseminating innovative data management methods related to smart city topics. While highlighting topics such as data visualization, a web-based ICT platform, and data-sharing methods, this book is ideally intended for researchers in the building industry, energy, and computer science fields; public administrators; building managers; and energy professionals along with practitioners, stakeholders, researchers, academicians, and students interested in the implementation of smart technologies for the built environment.